from sklearn_benchmarks.reporting.hp_match import HPMatchReporting
import pandas as pd
pd.set_option('display.max_colwidth', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
reporting = HPMatchReporting("sklearnex", config="config.yml")
reporting.make_report()
KNeighborsClassifier_brute_force¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=brute.
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | n_jobs | n_neighbors | accuracy_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.011 | 0.001 | NaN | 7.356 | 0.0 | -1 | 1 | NaN | 0.050 | 0.004 | 0.217 | 0.218 | See | See |
| 3 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.011 | 0.000 | NaN | 7.339 | 0.0 | -1 | 5 | NaN | 0.049 | 0.001 | 0.224 | 0.224 | See | See |
| 6 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.011 | 0.001 | NaN | 7.141 | 0.0 | 1 | 100 | NaN | 0.049 | 0.002 | 0.230 | 0.230 | See | See |
| 9 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.012 | 0.000 | NaN | 6.683 | 0.0 | -1 | 100 | NaN | 0.049 | 0.001 | 0.244 | 0.244 | See | See |
| 12 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.012 | 0.000 | NaN | 6.787 | 0.0 | 1 | 5 | NaN | 0.050 | 0.001 | 0.234 | 0.234 | See | See |
| 15 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.012 | 0.001 | NaN | 6.618 | 0.0 | 1 | 1 | NaN | 0.048 | 0.001 | 0.251 | 0.251 | See | See |
| 18 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.004 | 0.000 | NaN | 0.361 | 0.0 | -1 | 1 | NaN | 0.007 | 0.000 | 0.638 | 0.638 | See | See |
| 21 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.004 | 0.000 | NaN | 0.391 | 0.0 | -1 | 5 | NaN | 0.007 | 0.001 | 0.568 | 0.569 | See | See |
| 24 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.004 | 0.000 | NaN | 0.400 | 0.0 | 1 | 100 | NaN | 0.007 | 0.001 | 0.535 | 0.536 | See | See |
| 27 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.004 | 0.000 | NaN | 0.414 | 0.0 | -1 | 100 | NaN | 0.007 | 0.001 | 0.523 | 0.525 | See | See |
| 30 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.004 | 0.000 | NaN | 0.424 | 0.0 | 1 | 5 | NaN | 0.007 | 0.000 | 0.539 | 0.540 | See | See |
| 33 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.004 | 0.000 | NaN | 0.429 | 0.0 | 1 | 1 | NaN | 0.007 | 0.000 | 0.530 | 0.530 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | n_jobs | n_neighbors | accuracy_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 1.979 | 0.116 | NaN | 0.000 | 0.002 | -1 | 1 | 0.663 | 0.402 | 0.012 | 4.928 | 4.931 | See | See |
| 2 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.021 | 0.003 | NaN | 0.000 | 0.021 | -1 | 1 | 1.000 | 0.010 | 0.001 | 2.152 | 2.156 | See | See |
| 4 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.644 | 0.074 | NaN | 0.000 | 0.003 | -1 | 5 | 0.757 | 0.403 | 0.017 | 6.563 | 6.569 | See | See |
| 5 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.023 | 0.003 | NaN | 0.000 | 0.023 | -1 | 5 | 1.000 | 0.009 | 0.000 | 2.518 | 2.520 | See | See |
| 7 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.127 | 0.063 | NaN | 0.000 | 0.002 | 1 | 100 | 0.882 | 0.458 | 0.014 | 4.645 | 4.647 | See | See |
| 8 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.023 | 0.001 | NaN | 0.000 | 0.023 | 1 | 100 | 1.000 | 0.010 | 0.001 | 2.364 | 2.370 | See | See |
| 10 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.751 | 0.065 | NaN | 0.000 | 0.003 | -1 | 100 | 0.882 | 0.480 | 0.016 | 5.736 | 5.739 | See | See |
| 11 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.023 | 0.002 | NaN | 0.000 | 0.023 | -1 | 100 | 1.000 | 0.010 | 0.001 | 2.217 | 2.230 | See | See |
| 13 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.108 | 0.037 | NaN | 0.000 | 0.002 | 1 | 5 | 0.757 | 0.416 | 0.021 | 5.068 | 5.074 | See | See |
| 14 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.022 | 0.001 | NaN | 0.000 | 0.022 | 1 | 5 | 1.000 | 0.009 | 0.000 | 2.347 | 2.350 | See | See |
| 16 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 1.410 | 0.016 | NaN | 0.001 | 0.001 | 1 | 1 | 0.663 | 0.393 | 0.011 | 3.589 | 3.591 | See | See |
| 17 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.022 | 0.001 | NaN | 0.000 | 0.022 | 1 | 1 | 1.000 | 0.009 | 0.000 | 2.418 | 2.420 | See | See |
| 19 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.599 | 0.020 | NaN | 0.000 | 0.002 | -1 | 1 | 0.896 | 0.089 | 0.002 | 18.013 | 18.019 | See | See |
| 20 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.004 | 0.000 | NaN | 0.000 | 0.004 | -1 | 1 | 1.000 | 0.001 | 0.000 | 7.103 | 7.116 | See | See |
| 22 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.425 | 0.066 | NaN | 0.000 | 0.002 | -1 | 5 | 0.922 | 0.090 | 0.003 | 26.890 | 26.903 | See | See |
| 23 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.006 | 0.002 | NaN | 0.000 | 0.006 | -1 | 5 | 1.000 | 0.001 | 0.000 | 10.016 | 10.144 | See | See |
| 25 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.800 | 0.016 | NaN | 0.000 | 0.002 | 1 | 100 | 0.929 | 0.143 | 0.005 | 12.616 | 12.624 | See | See |
| 26 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.003 | 0.000 | NaN | 0.000 | 0.003 | 1 | 100 | 1.000 | 0.001 | 0.000 | 3.992 | 4.013 | See | See |
| 28 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.269 | 0.026 | NaN | 0.000 | 0.002 | -1 | 100 | 0.929 | 0.143 | 0.004 | 15.862 | 15.867 | See | See |
| 29 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.006 | 0.002 | NaN | 0.000 | 0.006 | -1 | 100 | 1.000 | 0.001 | 0.000 | 8.474 | 8.505 | See | See |
| 31 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.770 | 0.017 | NaN | 0.000 | 0.002 | 1 | 5 | 0.922 | 0.088 | 0.002 | 20.014 | 20.018 | See | See |
| 32 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.003 | 0.000 | NaN | 0.000 | 0.003 | 1 | 5 | 1.000 | 0.001 | 0.000 | 5.301 | 5.322 | See | See |
| 34 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.093 | 0.017 | NaN | 0.000 | 0.001 | 1 | 1 | 0.896 | 0.089 | 0.003 | 12.320 | 12.325 | See | See |
| 35 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.002 | 0.000 | NaN | 0.000 | 0.002 | 1 | 1 | 1.000 | 0.001 | 0.000 | 3.055 | 3.075 | See | See |
KNeighborsClassifier_kd_tree¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=kd_tree.
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | n_jobs | n_neighbors | accuracy_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 2.355 | 0.099 | NaN | 0.034 | 0.0 | -1 | 1 | NaN | 0.895 | 0.374 | 2.632 | 2.853 | See | See |
| 3 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.054 | 0.089 | NaN | 0.026 | 0.0 | -1 | 5 | NaN | 0.694 | 0.027 | 4.399 | 4.403 | See | See |
| 6 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.374 | 0.120 | NaN | 0.024 | 0.0 | 1 | 100 | NaN | 0.752 | 0.011 | 4.489 | 4.489 | See | See |
| 9 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.043 | 0.061 | NaN | 0.026 | 0.0 | -1 | 100 | NaN | 0.689 | 0.018 | 4.420 | 4.421 | See | See |
| 12 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.055 | 0.091 | NaN | 0.026 | 0.0 | 1 | 5 | NaN | 0.824 | 0.024 | 3.706 | 3.707 | See | See |
| 15 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.139 | 0.112 | NaN | 0.025 | 0.0 | 1 | 1 | NaN | 0.728 | 0.017 | 4.312 | 4.313 | See | See |
| 18 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.001 | NaN | 0.019 | 0.0 | -1 | 1 | NaN | 0.004 | 0.002 | 0.236 | 0.267 | See | See |
| 21 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | NaN | 0.026 | 0.0 | -1 | 5 | NaN | 0.002 | 0.001 | 0.311 | 0.381 | See | See |
| 24 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | NaN | 0.028 | 0.0 | 1 | 100 | NaN | 0.001 | 0.001 | 0.385 | 0.520 | See | See |
| 27 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | NaN | 0.030 | 0.0 | -1 | 100 | NaN | 0.001 | 0.000 | 0.480 | 0.487 | See | See |
| 30 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | NaN | 0.026 | 0.0 | 1 | 5 | NaN | 0.001 | 0.000 | 0.587 | 0.588 | See | See |
| 33 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | NaN | 0.031 | 0.0 | 1 | 1 | NaN | 0.001 | 0.000 | 0.522 | 0.523 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | n_jobs | n_neighbors | accuracy_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.805 | 1.139 | NaN | 0.000 | 0.001 | -1 | 1 | 0.929 | 0.113 | 0.005 | 7.145 | 7.154 | See | See |
| 2 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.003 | 0.000 | NaN | 0.000 | 0.003 | -1 | 1 | 1.000 | 0.000 | 0.000 | 8.852 | 9.044 | See | See |
| 4 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.971 | 0.400 | NaN | 0.000 | 0.001 | -1 | 5 | 0.946 | 0.185 | 0.006 | 5.238 | 5.241 | See | See |
| 5 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.003 | 0.000 | NaN | 0.000 | 0.003 | -1 | 5 | 1.000 | 0.000 | 0.000 | 6.903 | 7.125 | See | See |
| 7 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 5.202 | 0.717 | NaN | 0.000 | 0.005 | 1 | 100 | 0.951 | 0.604 | 0.024 | 8.609 | 8.616 | See | See |
| 8 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.003 | 0.001 | NaN | 0.000 | 0.003 | 1 | 100 | 1.000 | 0.001 | 0.000 | 2.678 | 2.767 | See | See |
| 10 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 3.073 | 0.383 | NaN | 0.000 | 0.003 | -1 | 100 | 0.951 | 0.617 | 0.023 | 4.985 | 4.988 | See | See |
| 11 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.004 | 0.001 | NaN | 0.000 | 0.004 | -1 | 100 | 1.000 | 0.001 | 0.000 | 4.683 | 4.833 | See | See |
| 13 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 1.627 | 0.364 | NaN | 0.000 | 0.002 | 1 | 5 | 0.946 | 0.215 | 0.006 | 7.553 | 7.557 | See | See |
| 14 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.001 | 0.000 | NaN | 0.000 | 0.001 | 1 | 5 | 1.000 | 0.001 | 0.000 | 2.845 | 2.908 | See | See |
| 16 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.797 | 0.333 | NaN | 0.000 | 0.001 | 1 | 1 | 0.929 | 0.111 | 0.002 | 7.155 | 7.156 | See | See |
| 17 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.001 | 0.000 | NaN | 0.000 | 0.001 | 1 | 1 | 1.000 | 0.000 | 0.000 | 3.281 | 3.390 | See | See |
| 19 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.033 | 0.020 | NaN | 0.000 | 0.000 | -1 | 1 | 0.891 | 0.001 | 0.000 | 55.223 | 55.300 | See | See |
| 20 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.003 | 0.000 | NaN | 0.000 | 0.003 | -1 | 1 | 1.000 | 0.000 | 0.000 | 20.515 | 20.914 | See | See |
| 22 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.026 | 0.002 | NaN | 0.001 | 0.000 | -1 | 5 | 0.911 | 0.001 | 0.000 | 30.187 | 30.211 | See | See |
| 23 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.002 | 0.000 | NaN | 0.000 | 0.002 | -1 | 5 | 1.000 | 0.000 | 0.000 | 13.952 | 14.178 | See | See |
| 25 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.036 | 0.008 | NaN | 0.000 | 0.000 | 1 | 100 | 0.894 | 0.006 | 0.000 | 6.120 | 6.122 | See | See |
| 26 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | NaN | 0.000 | 0.001 | 1 | 100 | 1.000 | 0.000 | 0.000 | 4.246 | 4.296 | See | See |
| 28 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.043 | 0.008 | NaN | 0.000 | 0.000 | -1 | 100 | 0.894 | 0.007 | 0.001 | 6.225 | 6.328 | See | See |
| 29 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.002 | 0.000 | NaN | 0.000 | 0.002 | -1 | 100 | 1.000 | 0.000 | 0.000 | 13.654 | 13.711 | See | See |
| 31 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.023 | 0.001 | NaN | 0.001 | 0.000 | 1 | 5 | 0.911 | 0.001 | 0.000 | 24.996 | 25.036 | See | See |
| 32 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | NaN | 0.000 | 0.001 | 1 | 5 | 1.000 | 0.000 | 0.000 | 4.362 | 4.434 | See | See |
| 34 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.022 | 0.003 | NaN | 0.001 | 0.000 | 1 | 1 | 0.891 | 0.001 | 0.000 | 36.620 | 37.005 | See | See |
| 35 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | NaN | 0.000 | 0.001 | 1 | 1 | 1.000 | 0.000 | 0.000 | 4.560 | 4.733 | See | See |
KMeans_tall¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=full, n_clusters=3, max_iter=30, n_init=1, tol=1e-16.
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | adjusted_rand_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_tall | fit | 1000000 | 1000000 | 2 | 0.563 | 0.076 | 30 | 0.028 | 0.0 | random | NaN | 0.287 | 0.015 | 1.960 | 1.962 | See | See |
| 3 | KMeans_tall | fit | 1000000 | 1000000 | 2 | 0.624 | 0.040 | 30 | 0.026 | 0.0 | k-means++ | NaN | 0.334 | 0.008 | 1.870 | 1.871 | See | See |
| 6 | KMeans_tall | fit | 1000000 | 1000000 | 100 | 6.972 | 0.317 | 30 | 0.115 | 0.0 | random | NaN | 3.741 | 0.121 | 1.864 | 1.865 | See | See |
| 9 | KMeans_tall | fit | 1000000 | 1000000 | 100 | 7.242 | 0.106 | 30 | 0.110 | 0.0 | k-means++ | NaN | 3.963 | 0.044 | 1.827 | 1.828 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | adjusted_rand_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_tall | predict | 1000000 | 1000 | 2 | 0.002 | 0.001 | 30 | 0.008 | 0.000 | random | 0.001 | 0.0 | 0.0 | 7.413 | 9.710 | See | See |
| 2 | KMeans_tall | predict | 1000000 | 1 | 2 | 0.002 | 0.000 | 30 | 0.000 | 0.002 | random | 1.000 | 0.0 | 0.0 | 12.420 | 12.483 | See | See |
| 4 | KMeans_tall | predict | 1000000 | 1000 | 2 | 0.002 | 0.000 | 30 | 0.008 | 0.000 | k-means++ | 0.001 | 0.0 | 0.0 | 9.524 | 9.836 | See | See |
| 5 | KMeans_tall | predict | 1000000 | 1 | 2 | 0.002 | 0.000 | 30 | 0.000 | 0.002 | k-means++ | 1.000 | 0.0 | 0.0 | 11.025 | 11.113 | See | See |
| 7 | KMeans_tall | predict | 1000000 | 1000 | 100 | 0.002 | 0.000 | 30 | 0.376 | 0.000 | random | 0.002 | 0.0 | 0.0 | 7.563 | 7.780 | See | See |
| 8 | KMeans_tall | predict | 1000000 | 1 | 100 | 0.002 | 0.000 | 30 | 0.000 | 0.002 | random | 1.000 | 0.0 | 0.0 | 11.454 | 11.566 | See | See |
| 10 | KMeans_tall | predict | 1000000 | 1000 | 100 | 0.002 | 0.000 | 30 | 0.385 | 0.000 | k-means++ | 0.002 | 0.0 | 0.0 | 7.724 | 7.923 | See | See |
| 11 | KMeans_tall | predict | 1000000 | 1 | 100 | 0.002 | 0.000 | 30 | 0.000 | 0.002 | k-means++ | 1.000 | 0.0 | 0.0 | 13.378 | 13.443 | See | See |
KMeans_short¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=full, n_clusters=300, max_iter=20, n_init=1, tol=1e-16.
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | adjusted_rand_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_short | fit | 10000 | 10000 | 2 | 0.101 | 0.004 | 20 | 0.002 | 0.0 | random | NaN | 0.054 | 0.004 | 1.876 | 1.881 | See | See |
| 3 | KMeans_short | fit | 10000 | 10000 | 2 | 0.309 | 0.006 | 20 | 0.001 | 0.0 | k-means++ | NaN | 0.141 | 0.003 | 2.195 | 2.196 | See | See |
| 6 | KMeans_short | fit | 10000 | 10000 | 100 | 0.337 | 0.015 | 20 | 0.024 | 0.0 | random | NaN | 0.264 | 0.008 | 1.280 | 1.281 | See | See |
| 9 | KMeans_short | fit | 10000 | 10000 | 100 | 1.145 | 0.013 | 20 | 0.007 | 0.0 | k-means++ | NaN | 0.635 | 0.010 | 1.802 | 1.803 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | adjusted_rand_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_short | predict | 10000 | 1000 | 2 | 0.002 | 0.000 | 20 | 0.007 | 0.000 | random | 0.000 | 0.001 | 0.0 | 3.312 | 3.327 | See | See |
| 2 | KMeans_short | predict | 10000 | 1 | 2 | 0.002 | 0.002 | 20 | 0.000 | 0.002 | random | 1.000 | 0.000 | 0.0 | 14.474 | 14.569 | See | See |
| 4 | KMeans_short | predict | 10000 | 1000 | 2 | 0.002 | 0.000 | 20 | 0.007 | 0.000 | k-means++ | 0.001 | 0.001 | 0.0 | 3.820 | 3.831 | See | See |
| 5 | KMeans_short | predict | 10000 | 1 | 2 | 0.002 | 0.000 | 20 | 0.000 | 0.002 | k-means++ | 1.000 | 0.000 | 0.0 | 11.974 | 12.037 | See | See |
| 7 | KMeans_short | predict | 10000 | 1000 | 100 | 0.003 | 0.000 | 20 | 0.235 | 0.000 | random | 0.279 | 0.002 | 0.0 | 2.247 | 2.253 | See | See |
| 8 | KMeans_short | predict | 10000 | 1 | 100 | 0.002 | 0.000 | 20 | 0.000 | 0.002 | random | 1.000 | 0.000 | 0.0 | 9.463 | 9.869 | See | See |
| 10 | KMeans_short | predict | 10000 | 1000 | 100 | 0.004 | 0.000 | 20 | 0.225 | 0.000 | k-means++ | 0.317 | 0.002 | 0.0 | 2.338 | 2.340 | See | See |
| 11 | KMeans_short | predict | 10000 | 1 | 100 | 0.002 | 0.000 | 20 | 0.000 | 0.002 | k-means++ | 1.000 | 0.000 | 0.0 | 9.562 | 9.705 | See | See |
LogisticRegression¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: penalty=l2, dual=False, tol=0.0001, C=1.0, fit_intercept=True, intercept_scaling=1, class_weight=nan, random_state=nan, solver=lbfgs, max_iter=100, multi_class=auto, verbose=0, warm_start=False, n_jobs=nan, l1_ratio=nan.
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | class_weight | l1_ratio | n_jobs | random_state | accuracy_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | LogisticRegression | fit | 1000000 | 1000000 | 100 | 15.785 | 0.381 | [20] | 0.051 | 0.000 | NaN | NaN | NaN | NaN | NaN | 2.801 | 0.038 | 5.635 | 5.635 | See | See |
| 3 | LogisticRegression | fit | 1000 | 1000 | 10000 | 1.433 | 0.602 | [26] | 0.056 | 0.001 | NaN | NaN | NaN | NaN | NaN | 1.087 | 0.037 | 1.318 | 1.319 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | class_weight | l1_ratio | n_jobs | random_state | accuracy_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | LogisticRegression | predict | 1000000 | 1000 | 100 | 0.001 | 0.001 | [20] | 1.386 | 0.0 | NaN | NaN | NaN | NaN | 0.56 | 0.001 | 0.001 | 0.716 | 1.375 | See | See |
| 2 | LogisticRegression | predict | 1000000 | 1 | 100 | 0.000 | 0.000 | [20] | 0.010 | 0.0 | NaN | NaN | NaN | NaN | 1.00 | 0.000 | 0.000 | 0.361 | 0.362 | See | See |
| 4 | LogisticRegression | predict | 1000 | 100 | 10000 | 0.003 | 0.000 | [26] | 3.199 | 0.0 | NaN | NaN | NaN | NaN | 0.35 | 0.004 | 0.001 | 0.598 | 0.616 | See | See |
| 5 | LogisticRegression | predict | 1000 | 1 | 10000 | 0.000 | 0.000 | [26] | 0.618 | 0.0 | NaN | NaN | NaN | NaN | 0.00 | 0.001 | 0.000 | 0.163 | 0.163 | See | See |
Ridge¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: alpha=1.0, fit_intercept=True, normalize=deprecated, copy_X=True, max_iter=nan, tol=0.001, solver=auto, random_state=nan.
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | max_iter | random_state | r2_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Ridge | fit | 1000 | 1000 | 10000 | 0.292 | 0.008 | NaN | 0.274 | 0.0 | NaN | NaN | NaN | 0.304 | 0.009 | 0.958 | 0.959 | See | See |
| 3 | Ridge | fit | 1000000 | 1000000 | 100 | 1.279 | 0.070 | NaN | 0.626 | 0.0 | NaN | NaN | NaN | 0.459 | 0.208 | 2.785 | 3.056 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | max_iter | random_state | r2_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Ridge | predict | 1000 | 1000 | 10000 | 0.011 | 0.001 | NaN | 7.616 | 0.0 | NaN | NaN | 0.083 | 0.019 | 0.001 | 0.546 | 0.547 | See | See |
| 2 | Ridge | predict | 1000 | 1 | 10000 | 0.000 | 0.000 | NaN | 0.879 | 0.0 | NaN | NaN | NaN | 0.000 | 0.000 | 0.602 | 0.614 | See | See |
| 4 | Ridge | predict | 1000000 | 1000 | 100 | 0.000 | 0.000 | NaN | 4.613 | 0.0 | NaN | NaN | 1.000 | 0.001 | 0.001 | 0.303 | 0.595 | See | See |
| 5 | Ridge | predict | 1000000 | 1 | 100 | 0.000 | 0.000 | NaN | 0.010 | 0.0 | NaN | NaN | NaN | 0.000 | 0.000 | 0.594 | 0.614 | See | See |